EP 4343571 A1 20240327 - VOICE-BASED PERFORMANCE QUERY WITH NON-SEMANTIC DATABASES
Title (en)
VOICE-BASED PERFORMANCE QUERY WITH NON-SEMANTIC DATABASES
Title (de)
SPRACHBASIERTE LEISTUNGSABFRAGE MIT NICHT-SEMANTIC-DATENBANKEN
Title (fr)
INTERROGATION VOCALE DE PERFORMANCE AVEC BASES DE DONNÉES NON SÉMANTIQUES
Publication
Application
Priority
US 202217950956 A 20220922
Abstract (en)
The use of natural language to query a database (e.g., storing performance data for an industrial system) is hindered by the use of non-semantic names for database elements in databases. While these non-semantic names could be modified, this requires modifying the databases, as well as modifying the applications that utilize the databases. Accordingly, embodiments disclosed herein train and apply a text-to-SQL model that translates natural-language queries into Structured Query Language (SQL) queries that utilize semantic names for database elements. These SQL queries utilize database views that map the native names for database elements to their semantic names. In addition, domain-specific pre-processing may be performed on the inputs to the text-to-SQL model. Collectively, this improves the accuracy of the text-to-SQL translation, without having to modify the databases or applications, while also enabling voice-based natural-language queries.
IPC 8 full level
G06F 16/242 (2019.01)
CPC (source: EP US)
G06F 16/243 (2019.01 - EP); G06F 16/24522 (2019.01 - US); G06F 16/24528 (2019.01 - US); G06F 16/24553 (2019.01 - US)
Citation (applicant)
- RUBIN ET AL.: "SmBoP: Semi-autoregressive Bottom-up Semantic Parsing", PROCEEDINGS OF THE 5TH WORKSHOP ON STRUCTURED PREDICTION FOR NLP, ASSOCIATION FOR COMPUTATIONAL LOGISTICS, August 2021 (2021-08-01), pages 12 - 21
- WANG ET AL.: "RAT-SQL: Relation-aware Schema Encoding and Linking for Text-to-SQL Parsers", PROCEEDINGS OF THE 58TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, 2020, pages 7567 - 7578
- YU ET AL.: "GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing", INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS, 2021
- VASWANI ET AL.: "Attention Is All You Need", ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS, 2017, pages 5998 - 6008
- WANG ET AL.: "Wake Word Detection with Streaming Transformers", 2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP, pages 5864 - 5868
Citation (search report)
- [I] RAMESH SANJAY ET AL: "A Semantic Data Model: Meaning Making from Data Structures in the SQL Server", JOURNAL OF INFORMATION SYSTEMS ENGINEERING AND BUSINESS INTELLIGENCE, vol. 4, no. 2, 28 October 2018 (2018-10-28), pages 106, XP093069726, ISSN: 2598-6333, Retrieved from the Internet <URL:https://e-journal.unair.ac.id/JISEBI/article/viewFile/8556/5664> DOI: 10.20473/jisebi.4.2.106-115
- [A] AYUSH KUMAR ET AL: "Deep Learning Driven Natural Languages Text to SQL Query Conversion: A Survey", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 8 August 2022 (2022-08-08), XP091291079
Designated contracting state (EPC)
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC ME MK MT NL NO PL PT RO RS SE SI SK SM TR
Designated extension state (EPC)
BA
Designated validation state (EPC)
KH MA MD TN
DOCDB simple family (publication)
DOCDB simple family (application)
EP 22204576 A 20221028; US 202217950956 A 20220922